This invention relates to call processing systems and, in particular, to a call center call routing process that utilizes: the identity of the calling party, the call context as well as a measurement of the effective agent skill level, comprising both the acquired and augmented skills of the various agents who staff the call center, to route the call to a destination call center agent in a manner that is appropriate to the contact, with the agent skill level being automatically updated on a dynamic basis.
It is a problem in customer service scenarios, such as a call center, that these systems are architected in a manner to minimize the cost of providing the offered services pursuant to some predefined level of responsiveness to customers"" requests. The call center systems typically provide a pool of customer service representatives, termed xe2x80x9cagentsxe2x80x9d herein, who have various skill levels, to provide the calling party with an appropriate response to their inquiry. The agents are managed by a call center administrator who manually generates metrics representative of various agent performance factors, including but not limited to: speed of processing the request, competence in providing the calling party with appropriate data, knowledge of the subject matter, and the like. Call center call routing systems use these metrics to interconnect a calling party with an agent who is determined to have the skills to most efficiently process the contact. The definition of these metrics and the efficiency measure are highly subjective and typically fail to recognize many other factors that are relevant to the processing of an incoming contact.
An incoming contact to a call center is traditionally processed through hunt groups to a selected one of a plurality of splits, each of which comprises a plurality of hard wired telephones wired into a queue. An improvement over this hard wired call distribution system comprises a universal work queue for agents, which enables the call center system administrator to adjust the assignment of the incoming call connections for each agent or group of agents while also monitoring call center statistics. Also, the agents who staff the call center are not dedicated to processing only a single type of contact, but can receive incoming calls of varying types, as their determined skill permits. The various agents and automated information sources available to the call center customer are dynamically incorporated into the communication connection on an as needed basis in order to serve the needs of the calling party.
In particular, the call center can be equipped with one or more automated resources that assist the agent in performing their assigned task. These automated resources are characterized by many different terms such as: automated knowledge access tools, knowledge management, knowledge base, guided problem solving tools, databases, expert systems, interactive diagnostic tools, and the like, which automated resources enable the agent to more efficiently analyze the calling party request and obtain closure with regard to providing the information and/or service necessary to satisfy the calling party, which actions are termed xe2x80x9cfulfillmentxe2x80x9d herein. The use of automated resources adds another dimension to the entire agent management process, since some agents have acquired their skills via experience and may not be adept at the use of the automated resources, while other agents are expert in their use of the automated resources while they do not have extensive experience in the topic area. Thus, the determination of the effective agent skill is a combination of the agent""s acquired skills, based upon actual experience, and the agent""s ability to use the each of the various automated resources that are part of the call center system, termed xe2x80x9caugmented skillxe2x80x9d herein. Existing call centers do not account for this additional dimension of agent management relating to augmented skills and the present systems use a simple multiple level skill assignment paradigm to differentiate only the agents"" acquired skills in performing their assigned tasks.
A further problem is that the assignment of the multiple skill levels is traditionally performed manually by the call center administrator capturing the agent""s skill level in various subject areas by monitoring the agent""s performance and then applying this information to call routing decisions. Unfortunately, the supervisor or call auditor must expend a significant amount of time in monitoring the agents and determining their competence using some set of quantifiable measurements. The resultant determined skill level is valid for only as long as the agent has not progressed to a successive level of competence in the skill sets. Thus, the measurement process must be ongoing and can require a significant administrative overhead. The absence of an automated skill level assignment system further complicates the presence of the automated resources in the call center environment.
In summary, existing call centers, equipped with automated resources which are used to serve the customers who access the call center, do not have the capability to recognize the effectiveness of the agents in their ability to use the automated resources or the ability to automatically determine and assess the skill level of the agents. This inability to effectively assess and/or automatically assign represent resource management problems that translate to additional expenses for the call center operator due to misallocation of agent resources to the incoming calls received at the call center.
The above described problems are solved and a technical advance achieved by the present system for integrating agent database access skills in call center agent assignment applications, which dynamically generates data indicative of an agent""s effective skill level by mapping the agent""s acquired skills into their augmented skills representative of their ability to use the various automated resources that are required to satisfy the customer""s request. The determined effective skill level is automatically updated as changes in the agent""s effective skills are measured and used by an intelligent work distribution system to make most effective use of the agents and their available skills.
In particular, in order to distribute work among the agents based upon agent skill levels, there must be a measure of each agent""s competence with a particular skill. This is presently done with acquired skills, but not with augmented skills. The use of automated automated resources in a call center environment is beneficial to the operator of the call center in that it reduces the cost of training customer agents and improves the overall effectiveness of the customer service agents. Thus, the pool of agents can be divided into categories of those who must use the guided problem solving tool to service a customer request, those who can address issues beyond the scope of the guided problem solving tool, and those who exhibit various levels of efficacy in using the guided problem solving tool. The granularity applied to each of these categories is a function of how the metric can be quantified and the need to have a predetermined number of skill levels to differentiate among the agents. The system for integrating agent database access skills in call center agent assignment applications automatically computes an agent""s effective skill level, which is a term used herein to describe a metric indicative of the agent""s overall knowledge management competence consisting of both acquired skills and augmented skills.
The present system weights an agent""s acquired skill level for a particular task by use of a weighting factor that is a measure of the agent""s augmented skill level consisting of the agent""s ability to use a guided problem solving tool. For example, the agent skill level associated with the use of a particular automated resource can be mapped to an effective skill level in a particular subject matter. The system automatically reevaluates and reassigns the skill levels for the agents with regard to the fulfillment process. There are numerous techniques that can be used to automatically update agent skill levels, including but not limited to:
Establishing a set of measurable per-transaction goals (sale made, contact handled within a predetermined time, customer satisfaction) for each interaction type of transaction (sales contact, trouble contact, emergency contact). If these goals are consistently met, the agent""s skill level is automatically incremented by a predefined amount.
Aggregating goal types over time such that the agent""s performance overtime is considered, with the agent performance representing consistency, as well as performance growth.
Reporting skill changes recorded in an external source and/or automatically generating alerts with respect to automatically identified changes in agent skills.
Thus, the present system for integrating agent database access skills in call center agent assignment applications dynamically generates data indicative of an agent""s effective skill level by mapping the agent""s experience skills into their ability to use the various automated resources that are required to satisfy the customer""s request. The determined effective skill level is automatically updated as changes in the agent""s effective skills are measured and used by an intelligent work distribution system to make most effective use of the agents and their available skills.